Stanley Osher

Updated on Jan 04, 2024

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Nationality American Fields Applied mathematics Education New York University		Role Mathematician Name Stanley Osher

Born April 24, 1942 (age 82) Brooklyn, New York, USA ( 1942-04-24 ) Institutions UCLA, SUNY, Stony Brook, UC Berkeley Doctoral students Moysey BrioLi-Tien ChengRon FedkiwFrederic GibouChiu-Yen KaoChi-Wang ShuMark SussmanYen-Hsi Richard TsaiHong-Kai Zhao Known for Level set methodShock capturing methodsimage processingL/TV methods Books Level Set Methods and Dynamic Implicit Surfaces Awards Carl Friedrich Gauss Prize Similar People Ronald Fedkiw, Chi‑Wang Shu, Jacob T Schwartz
Doctoral advisor Jacob T. Schwartz

3 20 2017 stanley osher

Stanley Osher (born April 24, 1942) is an American mathematician, known for his many contributions in shock capturing, level set methods, and PDE-based methods in computer vision and image processing. Osher is a professor at the University of California, Los Angeles (UCLA), Director of Special Projects in the Institute for Pure and Applied Mathematics (IPAM) and member of the California NanoSystems Institute (CNSI) at UCLA. He has a daughter, Kathryn, and a son, Joel.

Stanley Osher wwwimscuhkeduhktalkwithmasterssosherjpg

Stanley osher compressed sensing recovery algorithms and analysis

Education

Stanley Osher httpsplusmathsorgcontentsitesplusmathsor

B.S., Brooklyn College, 1962

M.S., New York University, 1964

Ph.D., New York University, 1966

Research interests

Level set methods for computing moving fronts

Approximation methods for hyperbolic conservation laws and Hamilton-Jacobi equations

Total variation(TV) and other PDE-based image processing techniques

Scientific computing

Applied partial differential equations

L¹/TV based convex optimization

Osher is listed as an ISI highly cited researcher.

Research contributions

Osher was the inventor (or co-inventor) and developer of many highly successful numerical methods for computational physics, image processing and other fields, including:

High resolution numerical schemes to compute flows having shocks and steep gradients, including ENO (essentially non-oscillatory) schemes (with Harten, Chakravarthy, Engquist, Shu), WENO (weighted ENO) schemes (with Liu and Chan), the Osher scheme, the Engquist-Osher scheme, and the Hamilton-Jacobi versions of these methods. These methods have been widely used in computational fluid dynamics (CFD) and related fields.

Total variation (TV) based image restoration (with Rudin and Fatemi) and shock ﬁlters (with Rudin). These are pioneering - and widely used - methods for PDE based image processing and have also been used for inverse problems.

Level set method (with Sethian) for capturing moving interfaces, which has been phenomenally successful as a key tool in PDE based image processing and computer vision, as well as applications in differential geometry, image segmentation, inverse problems, optimal design, Two-phase flow, crystal growth, deposition and etching.

Bregman iteration and augmented Lagrangian type methods for L¹ and L¹-related optimization problems which are fundamental to the ﬁelds of compressed sensing, matrix completion, robust principal component analysis, etc.

Overcoming the Curse of Dimensionality for Hamilton-Jacobi Equations arising in control theory and differential games.

Osher has founded (or co-founded) three successful companies:

Cognitech (with Rudin)

Level Set Systems

Luminescent Technologies (with Yablonovitch)

Osher has been a thesis advisor for at least 53 PhD students, with 188 descendants, as well as postdoctoral adviser and collaborator for many applied mathematicians. His Ph.D. students have been evenly distributed among academia and industry and labs, most of them are involved in applying mathematical and computational tools to industrial or scientiﬁc application areas.